Conceptual, methodological, and statistical challenges in brain imaging studies of developmentally based psychopathologies

Abstract

Brain imaging studies in developmentally based psychopathologies most often use magnetic resonance imaging (MRI) to study regional volumes, task-related activity, neurometabolite concentrations, or the paths of fiber tracts within the brain. Methodological challenges for the use of MRI in studying these disorders include understanding the ultrastructural correlates of brain structure and function that are below the limits of resolution of this imaging modality and developing better methods for approximating the anatomical boundaries of the cytoarchitectonic units that are defined by those ultrastructural characteristics. Conceptual challenges include distinguishing findings that represent pathophysiologically central causes from compensatory and epiphenomenal effects, a difficulty that stems directly from the inherently correlational nature of imaging data. The promise of functional imaging studies must capitalize on the specificity of the cognitive and behavioral probes that are used to illuminate core features of the pathophysiology of developmental disorders, while recognizing the assumptions and limitations of the subtraction paradigms that are used to isolate the brain functions of interest. Statistical challenges include incorporating adequate statistical models for scaling effects within the brain, as well as modeling important demographic correlates that contribute to the substantial interindividual variability inherent in most imaging data. Statistical analyses need to consider the substantial intercorrelation of measures across the brain and the importance of correcting for multiple statistical comparisons, as well as the need for improved methods for brain warping and for assessing effective connectivity in functional imaging studies.